AIMC Topic: Child, Preschool

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Classifying dysmorphic syndromes by using artificial neural network based hierarchical decision tree.

Australasian physical & engineering sciences in medicine May 1, 2018
Dysmorphic syndromes have different facial malformations. These malformations are significant to an early diagnosis of dysmorphic syndromes and contain distinctive information for face recognition. In this study we define the certain features of each...
Child, Preschool Child Image Processing, Computer-Assisted Humans Neural Networks, Computer Algorithms Infant Decision Trees Syndrome Face
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Multi-task prediction of infant cognitive scores from longitudinal incomplete neuroimaging data.

NeuroImage Apr 27, 2018
Early postnatal brain undergoes a stunning period of development. Over the past few years, research on dynamic infant brain development has received increased attention, exhibiting how important the early stages of a child's life are in terms of brai...
Female Male Child, Preschool Cognition Longitudinal Studies Child Development Neurodevelopmental Disorders Magnetic Resonance Imaging Humans Datasets as Topic Machine Learning Neuroimaging Brain
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Risk Assessment for Parents Who Suspect Their Child Has Autism Spectrum Disorder: Machine Learning Approach.

Journal of medical Internet research Apr 24, 2018
BACKGROUND: Parents are likely to seek Web-based communities to verify their suspicions of autism spectrum disorder markers in their child. Automated tools support human decisions in many domains and could therefore potentially support concerned pare...
Early Diagnosis Infant Surveys and Questionnaires Child, Preschool Parents Humans Machine Learning Mass Screening Autism Spectrum Disorder Female Male Risk Assessment
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ESMAC BEST PAPER 2017: Using machine learning to overcome challenges in GMFCS level assignment.

Gait & posture Apr 16, 2018
We used the random forest classifier to predict Gross Motor Function Classification System (GMFCS) levels I-IV from patient reported abilities recorded on the Gillette Functional Assessment Questionnaire (FAQ). The classifier exhibited outstanding ac...
Humans Machine Learning Retrospective Studies Female Male Surveys and Questionnaires Adolescent Cerebral Palsy Child, Preschool Child Motor Skills Disability Evaluation Activities of Daily Living
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The Dependence of Machine Learning on Electronic Medical Record Quality.

AMIA ... Annual Symposium proceedings. AMIA Symposium Apr 16, 2018
There is growing interest in applying machine learning methods to Electronic Medical Records (EMR). Across different institutions, however, EMR quality can vary widely. This work investigated the impact of this disparity on the performance of three a...
Logistic Models Hospitals, Pediatric Adolescent Los Angeles Humans Child, Preschool Data Accuracy Machine Learning Child Coronary Care Units Algorithms Hospital Mortality Electronic Health Records Intensive Care Units, Pediatric Infant
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Assessing patient risk of central line-associated bacteremia via machine learning.

American journal of infection control Apr 13, 2018
BACKGROUND: Central line-associated bloodstream infections (CLABSIs) contribute to increased morbidity, length of hospital stay, and cost. Despite progress in understanding the risk factors, there remains a need to accurately predict the risk of CLAB...
Adolescent Child, Preschool Child Bacteremia Catheterization, Central Venous Male Middle Aged Risk Assessment Infant Case-Control Studies Catheter-Related Infections Academic Medical Centers Epidemiologic Methods Humans Machine Learning Retrospective Studies Female Infant, Newborn Aged Aged, 80 and over Young Adult Adult
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Automated detection of focal cortical dysplasia type II with surface-based magnetic resonance imaging postprocessing and machine learning.

Epilepsia Apr 10, 2018
OBJECTIVE: Focal cortical dysplasia (FCD) is a major pathology in patients undergoing surgical resection to treat pharmacoresistant epilepsy. Magnetic resonance imaging (MRI) postprocessing methods may provide essential help for detection of FCD. In ...
Brain Female Young Adult Adult Sensitivity and Specificity Male Humans Machine Learning Middle Aged Magnetic Resonance Imaging Area Under Curve Adolescent Epilepsy Child, Preschool Neuroimaging Child Malformations of Cortical Development, Group I ROC Curve
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Transcriptomics and machine learning predict diagnosis and severity of growth hormone deficiency.

JCI insight Apr 5, 2018
BACKGROUND: The effect of gene expression data on diagnosis remains limited. Here, we show how diagnosis and classification of growth hormone deficiency (GHD) can be achieved from a single blood sample using a combination of transcriptomics and rando...
Gene Regulatory Networks Polymorphism, Single Nucleotide Predictive Value of Tests Principal Component Analysis Healthy Volunteers Human Growth Hormone Growth Disorders Child, Preschool Child ROC Curve Datasets as Topic Humans Severity of Illness Index Machine Learning Gene Expression Profiling Biomarkers Transcriptome Female Case-Control Studies Male Adolescent
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Healthcare-associated ventriculitis and meningitis in a neuro-ICU: Incidence and risk factors selected by machine learning approach.

Journal of critical care Mar 23, 2018
PURPOSE: To define the incidence of healthcare-associated ventriculitis and meningitis (HAVM) in the neuro-ICU and to identify HAVM risk factors using tree-based machine learning (ML) algorithms.
Meningitis, Bacterial Russia Craniotomy Cerebral Ventriculitis Incidence Child, Preschool Child Surgical Wound Infection Cross Infection Machine Learning Adult Female Prospective Studies Male Humans Risk Factors Middle Aged Intensive Care Units Young Adult Postoperative Complications Adolescent
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Development and validation of a diagnostic model for early differentiation of sepsis and non-infectious SIRS in critically ill children - a data-driven approach using machine-learning algorithms.

BMC pediatrics Mar 15, 2018
BACKGROUND: Since early antimicrobial therapy is mandatory in septic patients, immediate diagnosis and distinction from non-infectious SIRS is essential but hampered by the similarity of symptoms between both entities. We aimed to develop a diagnosti...
Infant Sepsis Humans Adolescent Systemic Inflammatory Response Syndrome Critical Illness Child, Preschool Follow-Up Studies Female Machine Learning Child Diagnosis, Differential Infant, Newborn Algorithms Early Diagnosis Reproducibility of Results Decision Support Techniques Male Prospective Studies
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